The error structure of time series cross-section hedonic models with sporadic event timing and serial correlation
针对房价特征价格模型中存在序列相关和销售时间不规则的问题，提出一个分解序列相关为事件和时间两个成分的模型，实证和模拟表明忽略零星相关会导致效率显著损失。
When estimating hedonic models of housing prices, the use of time series cross-section repeat sales data can provide improvements in estimator efficiency and correct for unobserved characteristics. However, in cases where serial correlation is present, the irregular timing of sales should also be considered. In this paper we develop a model that uses information on the timing of events to account for the sporadic occurrence of events. The model presumes that the serial correlation process can be decomposed into a time-independent (event-wise) component and a time-dependent (time-wise) component. Empirical tests cannot reject the presence of sporadic correlation patterns, while simulations show that the failure to account for sporadic correlation leads to significant losses in efficiency, and that the losses from ignoring sporadic correlation when it exists are larger than losses when sporadic correlation is falsely assumed. Copyright © 1999 John Wiley & Sons, Ltd.